SI Cortical Contributions to Tactile Motion Perception

Abstract

The specific aim of this project was to test the hypothesis (through parallel neurophysiological experiments and neural network modeling simulations) that perceptual mislocalization of a moving tactile stimulus arises from a systematic misrepresentation of stimulus location on the skin by primary somatosensory cerebral cortex (SI). Experimentally, SI cortical experiments substantiated the original hypothesis by demonstrating that the pattern of neural activity evoked in SI cortex by a moving skin stimulus varies with stimulus velocity in a manner paralleling that of perception. In the modeling studies, a novel model of synaptic input integration by dendrites of cortical pyramidal cells was developed which enables cells to tune to higher-order stimulus features. Studies with the model also supported the original hypothesis. Additionally, this network model was tested for its ability to extract higher order features of sensory input patterns, and it was shown to be very successful at extending current techniques of nonlinear factor analysis. In this progress report, we demonstrate its use in automatic target recognition, or more specifically, in recognizing military vehicles in real-world settings.

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Document Details

Document Type
Technical Report
Publication Date
Jul 21, 2006
Accession Number
ADA455252

Entities

People

  • Mark Tommerdahl

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Automata Theory
  • Brain
  • Cerebral Cortex
  • Computational Science
  • Computer Languages
  • Engineering
  • Factor Analysis
  • Machine Learning
  • Military Vehicles
  • Neural Networks
  • Neurons
  • Recognition
  • Scientists
  • Supervised Machine Learning
  • Target Recognition

Fields of Study

  • Biology
  • Psychology

Readers

  • Computational Modeling and Simulation
  • Neuroscience
  • Vision Science/Vision Psychology/Cognitive Neuroscience.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference